Revolutionizing Agriculture With A IOT: Applications, Challenges, And Future Directions
Keywords:
Artificial Intelligence (AI),, Internet of Things (IoT),, smart agriculture, precision farming, sustainable agriculture, machine learning, predictive analytics, resource optimization, cybersecurity, blockchainAbstract
The combination of Artificial Intelligence (AI) and the Internet of Things (IoT) — AIoT — is changing the way agriculture is done through data-driven decisions. AIoT-based examples in smart precision farming, livestock tracking, greenhouse automation and supply chain traceability are presented in this study, which results in improved resource efficiency, crop yields and food safety. The key technologies involved are IoT sensors and drones, machine learning algorithms, and predictive analytics that are used to reduce water, fertiliser, and pesticide and allow early detection of pests and diseases. However, because of its potential hurdles, such as high
implementation cost, data security risk and the technical literacy of the farmers. Finally, the research is advocative towards the use of costeffective AIoT solutions, robust cybersecurity frameworks and user-friendly interfaces for accelerated sustainable farming. The key for the next generation of agriculture is the integration of blockchain, autonomous farming systems and climate-resilient AI models.
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References
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